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Job Description

Role Summary

Lead the strategy, platform build-out, and adoption of AI/ML across Research for global digital transformation effort, making AI agents, models, and tools a daily, accessible part of wet‑lab and dry‑lab scientists’ workflows. Translate AF priorities into a practical, compliant AI services layer—data foundations, MLOps, agentic assistants, model governance, and change enablement—that shortens time from experiment to insight and elevates decision quality across discovery programs.

Objectives / Purpose

• Define and execute a multi‑year AI/ML roadmap aligned to Research use cases and KPIs.
• Establish an AI‑ready data foundation (FAIR-by-design) and scientist‑facing AI tools embedded in ELN/LIMS/instrument workflows.
• Institutionalize Responsible AI & GxP-aware governance for production models.
• Drive adoption through super-user networks, training, and change management to achieve measurable value and ROI.

Scope / Impact

Global Research scope with cross‑site collaboration (US/EU/JP). Direct impact on data-to-decision latency, assay/analysis reproducibility, and portfolio productivity. Partner with operations, Computational Sciences & Data Strategy, IT, function leads, and platform teams to deliver outcomes at scale.

Accountabilities

Strategy & Roadmap

• Own Research’s AI/ML strategy and sequencing (MVP → scale) across wet‑lab ↔ dry‑lab integration and self‑service tools.
• Align priorities with Research’s KPIs and portfolio goals; establish and monitor achievement of success criteria and milestones.

Platform, Data & Integration

• Guide the development of AI‑ready data foundations (provenance, metadata/ontologies, harmonization) across ELN/LIMS, instruments, imaging, and omics.
• Integrate platforms (e.g., ELN, SDMS & AI Cloud) to liberate, contextualize, and operationalize lab data for AI/ML.
• Stand up modern MLOps (CI/CD, registries, experiment tracking, monitoring) and secure service/APIs embedded in workflows.

Agentic AI & Productization

• Design self-service and user-friendly processes for deployment of AI agents for scientists (literature triage, protocol assist, data QC, analysis pipelines, code helpers).
• Guide engineering efforts to deliver production models (e.g., sequence/structure prediction, assay QC, outlier detection, multimodal analytics).

Adoption & Change Enablement

• Lead adoption via super‑user networks, training, and communications; co‑own readiness plans with NCSP.
• Work with Change Management leads to publish playbooks and guardrails enabling self‑service AI workflows for scientists.

Governance, Risk & Compliance

• Define and Implement Responsible AI and risk‑based governance (ALCOA+, validation mindset, audit trails, XAI, privacy/PII controls).

Impact & Reporting

• Own measurable impact (adoption, latency, reproducibility, ROI) and provide transparent reporting to R&D leadership and key stakeholders.

Qualifications

Required

• Advanced degree in Computer Science, AI/ML, Computational Biology/Chemistry, Bioinformatics, or related; or equivalent industry experience.
• 10+ years in AI/ML for life sciences; 5+ years strategic leadership delivering production AI in scientific environments.
• Proven MLOps platform build and delivery of scientist‑facing AI tools embedded in ELN/LIMS/instrument workflows.
• Expertise in FAIR data, scientific data models/ontologies, and integration across wet‑lab instruments, imaging, and omics.
• Experience with Responsible AI and GxP‑adjacent validation/governance in pharma/biotech R&D.
• Strong stakeholder management; ability to translate complex science/data into usable AI for end users.

Preferred

• Experience working in wet-labs and knowledge of Research and Development workflows and processes in either the biologics and/or small molecule fields
• Agentic AI systems and LLMs for scientific contexts; multimodal ML (text/images/sequences/numerical).
• Knowledge of Research/Pharma Sci common data models and cloud analytics/HPC integrations.

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.

For Location:

Boston, MA

U.S. Base Salary Range:

$174,500.00 - $274,230.00

The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. 

U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation. 

EEO Statement

Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.

Locations

Boston, MA

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

Job Exempt

Yes

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.